Working strategy in the AI era: skills in higher demand, and what's actually changing
Generative AI is now used across many types of work, from writing reports and summarising data to drafting designs and helping write code. The question is no longer "will AI affect my job", but "which parts of my job will change, and which skills should I build first".
Resmi.ID Team · 6 min read ·
Photo: Adam Satria / Unsplash
This article sums up what's actually changing, the skills employers are increasingly looking for, and practical steps you can start now, whatever field you work in.
What's changing: tasks, not always entire jobs
LinkedIn's Economic Graph research projects that the skills needed for most jobs will change significantly by 2030, with AI development as one of the main drivers. That means a job title can stay the same while how it's done, and the tools used to do it, change faster than before.
This pattern is easier to understand as a shift in tasks rather than entire roles disappearing. Tasks that are repetitive and follow a fixed pattern, such as summarising long documents, drafting a first version of a piece of writing, or sorting data, get assisted by AI faster. Tasks that require judgment on unique situations, building trust with other people, or accountability for final decisions remain much harder to fully replace.
Skills employers are increasingly looking for
PwC's analysis of nearly a billion job ads worldwide found that workers with advanced AI skills, such as machine learning or prompt engineering, earned an average wage premium of 56% in 2024, up from 25% the year before. That means knowing how to apply AI within your own field is starting to carry real market value, not just a nice line on a CV.
- Using AI tools for everyday work: writing clear prompts, checking AI output before relying on it, and knowing when AI isn't the right tool for the job.
- Critical thinking and fact-checking: AI can produce confident-sounding information that's wrong, so the ability to verify before using its output matters more than ever.
- Communication and collaboration: explaining ideas, negotiating, and working across teams remain hard for AI to fully replicate.
- Adaptability — learning new things quickly: tools and ways of working change more often, so a habit of continuous learning matters more than mastering one specific tool forever.
- Deep knowledge in your own field: AI helps speed up work, but still needs someone who understands the business context, rules, and customer needs in that field to judge the output.
Professions most exposed, and those relatively safer
There's no definitive list that applies to every country, since the speed and way AI gets adopted differs by industry. But the general direction is fairly consistent across reports: jobs with highly structured, repetitive tasks, such as data entry, routine document summarising, or customer support handling the same repeated questions, get assisted or partly replaced by AI tools faster.
On the other hand, jobs that rely on direct human relationships (healthcare, teaching, counselling), decisions carrying legal or safety responsibility (medicine, law, construction), and physical field work that's hard to map into data (equipment repair, field logistics, service work), are relatively safer in the near term. This isn't a permanent guarantee — it reflects the kind of tasks that currently dominate those jobs.
In Indonesia, the Ministry of Manpower (Kemnaker) takes the view that AI adoption at work should be human-centred: AI is meant to strengthen workers' abilities rather than simply replace them, applied participatively together with workers. Kemnaker is also expanding vocational training that includes AI literacy and data analysis, and has formed training partnerships with several industry players to build AI talent.
Concrete steps to stay relevant
- 1Try AI tools in your own fieldStart with a small, repetitive task in your job, then notice which parts it genuinely helps with.
- 2Learn the basics, not just how to use itSpend time understanding how generative AI actually works, rather than only following one tool's tutorial that may change anytime.
- 3Strengthen hard-to-replicate skillsPractice explaining ideas verbally and in writing, leading discussions, and making decisions in non-standard situations.
- 4Join structured trainingLook for vocational training or certifications relevant to your field, including government training programmes that increasingly include AI literacy.
- 5Document your work's impactRecord achievements that show your human judgment and accountability, not just output a tool could have produced.
- 6Check job listings regularlyNotice new skills that start appearing in job descriptions, as an early signal of where your industry is heading.
On Resmi.ID Karir, you can save a search for your target role and get notified by WhatsApp or email as soon as a matching job is posted. From there, you can also track which skills keep appearing in job descriptions in your field, as input for deciding which skills to strengthen first.
Conclusion
AI is changing how a lot of work gets done, especially tasks that are repetitive and follow a fixed pattern. The skills gaining the most value aren't simply "knowing how to use AI" — they're a combination of understanding how AI works, thinking critically about its output, and staying strong in skills that rely on judgment and human connection. Start small: try a tool relevant to your work, then strengthen the skills no tool can easily replicate.
References
- LinkedIn Economic Graph — AI at Work: Here's What's Changing
- PwC — 2025 Global AI Jobs Barometer
- Kemnaker — Menaker: Adopsi AI di Dunia Kerja Harus Berorientasi pada Manusia
This information is general. For important decisions, check the latest rules at official sources or consult the relevant authorities.
